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Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment

Wong, CW and Olafsson, V and Plank, M and Snider, J and Halgren, E and Poizner, H and Liu, TT (2014) Resting-state fMRI activity predicts unsupervised learning and memory in an immersive virtual reality environment. PLoS ONE, 9 (10).

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Abstract

© 2014 Wong et al. In the real world, learning often proceeds in an unsupervised manner without explicit instructions or feedback. In this study, we employed an experimental paradigm in which subjects explored an immersive virtual reality environment on each of two days. On day 1, subjects implicitly learned the location of 39 objects in an unsupervised fashion. On day 2, the locations of some of the objects were changed, and object location recall performance was assessed and found to vary across subjects. As prior work had shown that functional magnetic resonance imaging (fMRI) measures of resting-state brain activity can predict various measures of brain performance across individuals, we examined whether resting-state fMRI measures could be used to predict object location recall performance. We found a significant correlation between performance and the variability of the resting-state fMRI signal in the basal ganglia, hippocampus, amygdala, thalamus, insula, and regions in the frontal and temporal lobes, regions important for spatial exploration, learning, memory, and decision making. In addition, performance was significantly correlated with resting-state fMRI connectivity between the left caudate and the right fusiform gyrus, lateral occipital complex, and superior temporal gyrus. Given the basal ganglia's role in exploration, these findings suggest that tighter integration of the brain systems responsible for exploration and visuospatial processing may be critical for learning in a complex environment.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Wong, CW
Olafsson, V
Plank, M
Snider, J
Halgren, E
Poizner, H
Liu, TT
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorHayasaka, SatoruUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Centers: Other Centers, Institutes, or Units > McGowan Institute for Regenerative Medicine
Date: 6 October 2014
Date Type: Publication
Journal or Publication Title: PLoS ONE
Volume: 9
Number: 10
DOI or Unique Handle: 10.1371/journal.pone.0109622
Refereed: Yes
Other ID: NLM PMC4186845
PubMed Central ID: PMC4186845
PubMed ID: 25286145
Date Deposited: 12 May 2015 17:56
Last Modified: 29 Jan 2019 15:55
URI: http://d-scholarship.pitt.edu/id/eprint/24027

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